I-Corps Teams: STEM Skills Genome

I-Corps 团队：STEM 技能基因组

• 批准号: 1903859
• 负责人: Rhonda Shrader
• 金额: $ 5万
• 依托单位: University of California-Berkeley
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-02-01 至 2020-01-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1903859&HistoricalAwards=false
• 关键词: Corps; Teams; STEM; Skills; Genome

The broader impact/commercial potential of this I-Corps project is to increase student and eventually, employee engagement, by better aligning skills and innate interests with degree programs, particularly novel STEM programs. In response to increasing demand for new types of jobs, degree programs such as Computational Genomics and Music Technology have combined fields that have historically been distinct. This project enables students to discover both traditional and emerging majors relevant to them. By providing actionable insights and better alignment of interests early on, this decreases the friction of changing majors (~80% currently) during college and begins to mitigate widespread lack of engagement (~70%) in the workplace. Compared with traditional methods that match GPAs, test scores, unstructured essays, and resumes, with schools, majors, and job openings, this project could revolutionize the way students identify, train and prepare for their future careers.This I-Corps project is based on a novel patent-pending technology of a unified multi-dimensional data representation method called Skills Genome. Skills Genome can be exploited by several machine learning models, allowing for capturing and modeling complex student data inputs such as critical thinking, communication, interests, leadership, etc. with temporal graphs. By making the structure of the graph accessible to several machine learning models, the method improves accuracy, relevance and facilitates scale. Specifically, this tracks the student?s development timeline, so they can best determine the timing and sequencing of skills needed for their chosen careers. Further, by matching profiles at scale, new insights into potential careers can be surfaced, along with the next steps needed to achieve them.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

这个I-Corps项目的更广泛的影响/商业潜力是通过更好地使员工参与度增加学生，并通过更好地使技能和天生的兴趣与学位课程（尤其是新型STEM计划）保持一致。为了响应对新型工作类型的需求不断增长，计算基因组学和音乐技术等学位课程已将历史上与众不同的领域结合在一起。 该项目使学生能够发现与他们相关的传统和新兴专业。通过提供可行的见解和更好地对齐利益，这减少了大学期间改变专业的摩擦（约80％），并开始减轻工作场所中广泛缺乏参与度（约70％）。 与传统的方法相比，与学校，专业和职位空缺相匹配的传统方法，该项目可以彻底改变学生对未来职业的识别，训练和准备的方式。该I-Corps项目基于一种新颖的专利申请的技术，该技术是一种统一的多维数据代表方法，称为“技能基因”。几种机器学习模型可以利用技能基因组，从而可以通过时间图捕获和建模复杂的学生数据输入，例如批判性思维，沟通，兴趣，领导等。 通过使几种机器学习模型可以访问图的结构，该方法提高了准确性，相关性和促进规模。 具体来说，这跟踪了学生的发展时间表，因此他们可以最好地确定所选职业所需的技能的时机和测序。 此外，通过大规模匹配概况，可以浮出水面的新见解，以及实现这些职业所需的下一步措施。该奖项反映了NSF的法定任务，并被认为是值得通过基金会的知识分子和更广泛影响的评估评估标准通过评估来获得支持的。